トルク制御脚式ロボットのためのフィードバックMPC
Feedback MPC for Torque-Controlled Legged Robots
DDPベースのMPCに緩和バリア関数と周波数依存コストを組み合わせ、低い更新レートでもトルク制御四脚ロボットANYmalの安定した歩行を実現した。
著者: Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter
分類: cs.RO
原文アブストラクト
The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynamic systems such as legged robots. This problem is commonly circumvented by using a fast tracking controller to compensate for model errors between updates. In this work, we show that the feedback policy from a Differential Dynamic Programming (DDP) based MPC algorithm is a viable alternative to bridge the gap between the low MPC update rate and the actuation command rate. We propose to augment the DDP approach with a relaxed barrier function to address inequality constraints arising from the friction cone. A frequency-dependent cost function is used to reduce the sensitivity to high-frequency model errors and actuator bandwidth limits. We demonstrate that our approach can find stable locomotion policies for the torque-controlled quadruped, ANYmal, both in simulation and on hardware.
